Lecture 1

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ISEN 315
Spring 2011
Dr. Gary Gaukler
Marketing
Operations
Finance
Functional Areas of the Firm
Time Horizons for Decisions
1. Long Term Decisions
2. Intermediate Term Decisions
3. Short Term Decisions
The Elements of Production and
Operations Strategy
History of POM
Early years of the Industrial Revolution 1780-1890
– Shift from low-volume production to large scale
operations
Mass Production 1890-1920
– Concept of the assembly line
– Frederick Taylor champions the idea of “scientific
management”
– “The first IE”
“Golden Age” of IE 1920-1960
– Operations Research and IE influence industry
– Inventory control, quality control, scheduling
History of POM
1960-1990
– Sophisticated concepts: Quality Circles, JIT
– US companies lose competitive edge
1990-today
– Supply chain management
– New technologies: internet, wireless, RFID
How Do Firms Differentiate Themselves
from Competitors?
• Low Cost Leaders: Some examples include
• High Quality (and price) Leaders. Ex:
Along What Other Dimensions Do Firms
Compete?
The Product Life-Cycle Curve
A First Operations Model: Capacity
Strategy
Fundamental issues:
– Amount. When adding capacity, what is the optimal
amount to add?
• Too little
• Too much
– Timing. What is the optimal time between adding
new capacity?
– Type. Level of flexibility, automation, layout,
process, level of customization, outsourcing, etc.
Three Approaches to Capacity Strategy
• Policy A: Try not to run short. Here capacity
must lead demand, so on average there will
be excess capacity.
• Policy B: Build to forecast. Capacity additions
should be timed so that the firm has excess
capacity half the time and is short half the
time.
• Policy C: Maximize capacity utilization.
Capacity additions lag demand, so that
average demand is never met.
Capacity Leading and Lagging Demand
Determinants of Capacity Strategy
• Highly competitive industries (commodities, large
number of suppliers, limited functional difference in
products, time sensitive customers) – here shortages
are very costly.
• Monopolistic environment where manufacturer has
power over the industry: (Intel, Lockheed/Martin).
• Products that obsolete quickly, such as computer
products. Want type C policy, but in competitive
industry, such as computers, you will be gone if you
cannot meet customer demand. Need best of both
worlds: Dell Computer.
Mathematical Model for Timing of Capacity
Additions (Capacity leads demand)
Let D = Annual Increase in Demand
x = Time interval between adding capacity
r = annual discount rate (compounded
continuously)
f(y) = Cost of expanding by capacity y
Mathematical Model (continued)
• A typical form for the cost function f(y) is:
f ( y)  ky
a
Where k is a constant of proportionality, and a
measures the ratio of incremental to average cost of
a unit of plant capacity.
Capacity Expansion Cost
Dynamic Capacity Expansion
Suppose demand exhibits a linear trend:
y: current demand (= current capacity)
D: rate of increase per unit time
Dynamic Capacity Expansion
Capacity leads demand
Dynamic Capacity Expansion
Question: What value of x minimizes the net present value
of capacity expansion costs?
x = time interval between capacity expansions
Model Assumptions
•
•
•
•
•
•
•
•
Infinite planning horizon
Demand grows linearly
Capacity expansion allowed at any time point
Any size capacity expansion allowed
No shortages allowed
Continuous discounting at rate r
Capacity expansion is instantaneous
Expansion cost for expanding by size x is f(x)=kxa
(0<a<1)
Continuous Discounting
• The present value of $1 incurred in t years, assuming
continuous compounding at a rate r, is e-rt
• Let’s derive this!
Optimal Expansion Size
• Need to satisfy all demands
• x is the time interval between expansions
• Hence, at the time of expansion, the expansion size
should be:
• Cash flows:
Sum of Discounted Costs
• Cost = C(x) = f(xD) + f(xD)e-rx + f(xD)e-2rx + ...
• After some algebra:
– Cost = C(x) = f(xD)/(1-e-rx)
• Want to find: min C(x) s.t. x>=0
• Result: rx / (erx-1) – a = 0
• Numerical solution only!
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